One of the many tools that administrators use on a daily basis is the Windows Command Line / Prompt. Over this course, you'll learn the following skills, which are often used in the real world: 
 
* How to create, rename, move and delete files and directories. 
 
* The different types of file systems and how to navigate between directories 
 
* Setting the date and time on your PC using the date, time and tzutil commands 
 
* Managing and formatting disk drives using the Diskpart command 
 
* Shutting down, restarting and logging off your machine 
 
* Viewing and applying group policy information using the Gpupdate and Gpresult commands 
 
* Creating batch files and some of the most common commands used within them. 
 
* How to access Windows Management Instrumentation database (WMI) information using the WMIC command 
 
Whilst there are some differences between versions of Windows, a lot of these commands haven't changed since Windows 2000, meaning that any prior knowledge of this subject, while not essential by any means, would be advantageous.

English

Command Prompt Overview

Command Prompt Overview

Creating Files &amp; Directories

Creating Files & Directories

Renaming &amp; Moving Files &amp; Directories

Renaming & Moving Files & Directories

Deleting Files and Directories

Deleting Files and Directories

File Systems &amp; Directory Navigation

File Systems & Directory Navigation

Viewing Directory Structures with DIR &amp; TREE

Viewing Directory Structures with DIR & TREE

Setting Date and Time

Setting Date and Time

Disk Management with Diskpart - Part 1

Disk Management with Diskpart - Part 1

Disk Management with Diskpart - Part 2

Disk Management with Diskpart - Part 2

Gpupdate command

Gpresult command

Formatting Disk Drives

Formatting Disk Drives

Shutting Down, Restarting and Logging Off

Shutting Down, Restarting and Logging Off

Creating Batch Files

Creating Batch Files

WMIC Command Overview

WMIC Command Overview

Windows Command Line (cmd) & Batch Script Management

Desktop Support Engineer

Tier 1

Youtube is the second search engine in the world and is always taking new VIDEO CREATORS, do you want to be one of them? 
 
In This Course You will learn How to Create a YOUTUBE Channel from ZERO and we will make it attractive for your future followers making a good Banner, a proper description, Keywords and TAGS. 
 
Also, You will learn the best way to Upload videos, how to create attractive THUMBNAILS, How to use properly the keywords in your uploads and more. 
 
We will learn everything about the YOUTUBE platform and all the secrets inside the famous YOUTUBE algorithm, how the YOUTUBE SEO works and I will give you all the tips and techniques that you need to grow as a youtuber. 
 
Are you ready to be a YOUTUBER? What are you waiting for? I'll see you in class.

Youtube Masterclass: Create A YouTube Channel From Scratch

Photographer/videographer/Youtuber

Other

Technology

Error

Tier 3

Video Design

Digital Photography

Photography Tools

Commercial Photography

Photography

ILSVRC stands for Imagenet Large Scale Visual Recognition Challenge or the Imagenet Challenge.

ILSVRC is a challenge that is held annually to allow contenders to classify the images correctly and generate the best possible predictions.

AlexNet CNN architecture won the 2012 ImageNet ILSVRC challenge by a large margin: it achieves a top-five error rate of 17% while the second-best achieved only 26%

It was developed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton.

It is quite similar to LeNet-5, only much larger and deeper, and it was the first to stack convolutional layers directly on top of each other, instead of stacking a pooling layer on top of each convolutional layer.

It consists of 8 convolution land fully connected layers and 3 max-pooling layers.

To reduce overfitting, the authors used two regularization techniques: first, they applied dropout with a 50% dropout rate during training to the outputs of layers F8 and F9. Second, they performed data augmentation by randomly shifting the training images by various offsets, flipping them horizontally, and changing the lighting conditions.

ZFNet is another 8-layer CNN architecture.

ZFNet is largely similar to AlexNet, with the exception of a few of the layers.

ZFNet CNN architecture won the 2013 ImageNet ILSVRC challenge.

One major difference in the approaches was that ZF Net used 7x7 sized filters whereas AlexNet used 11x11 filters.

The intuition behind this is that by using bigger filters we were losing a lot of pixel information, which we can retain by having smaller filter sizes in the earlier convolution layers.

The number of filters increases as we go deeper. This network also used ReLUs for their activation and trained using batch stochastic gradient descent.

The runner-up in the ILSVRC 2014 challenge was VGGNet.

It was developed by K. Simon‐yan and A. Zisserman.

During the design of the VGGNet, it was found that alternating convolution & pooling layers were not required. So VGGnet uses multiple Convolutional layers in sequence with pooling layers in between.

It had a very simple and classical architecture, with 2 or 3 convolutional layers, a pooling layer, then again 2 or 3 convolutional layers, a pooling layer, and so on (with a total of just 16 convolutional layers), plus a final dense net‐work with 2 hidden layers and the output layer. It used only 3 × 3 filters, but many filters.

The GoogLeNet architecture was developed by Christian Szegedy et al. from Google Research,12 and it won the ILSVRC 2014 challenge by pushing the top-5 error rate below 7%.

This great performance came in large part from the fact that the network was much deeper than previous CNNs

This was made possible by sub-networks called inception modules, which allow GoogLeNet to use parameters much more efficiently than previous architectures: GoogLeNet actually has 10 times fewer parameters than AlexNet (roughly 6 million instead of 60 million).

GoogLeNet uses 9 inception modules and it eliminates all fully connected layers using average pooling to go from 7x7x1024 to 1x1x1024. This saves a lot of parameters.

Several variants of the GoogLeNet architecture were later proposed by Google researchers, including Inception-v3 and Inception-v4, using slightly different inception modules, and reaching even better performance.

The ILSVRC 2015 challenge was won using a Residual Network (or ResNet)

It delivered an astounding top-5 error rate under 3.6%, using an extremely deep CNN composed of 152 layers. It confirmed the general trend: models are getting deeper and deeper, with fewer and fewer parameters. The key to being able to train such a deep network is to use skip connections (also called shortcut connections): the signal feeding into a layer is also added to the output of a layer located a bit higher up the stack. Let’s see why this is useful.

When training a neural network, the goal is to make it model a target function h(x). If you add the input x to the output of the network (i.e., you add a skip connection), then the network will be forced to model f(x) = h(x)-x rather than h(x). This is called residual learning.

<ol>
 <li>ILSVRC’10</li>
 <li>ILSVRC’11</li>
 <li>ILSVRC’12 (AlexNet)</li>
 <li>ILSVRC’13 (ZFNet)</li>
 <li>ILSVRC’14 (VGGNet)</li>
 <li>ILSVRC’14 (GoogleNet)</li>
 <li>ILSVRC’15 (ResNet)</li>
</ol>
<ul>
 <li>ILSVRC stands for Imagenet Large Scale Visual Recognition Challenge or the Imagenet Challenge.</li>
 <li>ILSVRC is a challenge that is held annually to allow contenders to classify the images correctly and generate the best possible predictions.</li>
</ul>
<h2>AlexNet</h2>
 
<figure>&nbsp;</figure>
<ul>
 <li>AlexNet CNN architecture won the 2012 ImageNet ILSVRC challenge by a large margin: it achieves a top-five error rate of 17% while the second-best achieved only 26%</li>
 <li>It was developed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton.</li>
 <li>It is quite similar to LeNet-5, only much larger and deeper, and it was the first to stack convolutional layers directly on top of each other, instead of stacking a pooling layer on top of each convolutional layer.</li>
 <li>It consists of 8 convolution land fully connected layers and 3 max-pooling layers.</li>
</ul>
 
<figure>&nbsp;</figure>
To reduce overfitting, the authors used two regularization techniques: first, they applied dropout with a 50% dropout rate during training to the outputs of layers F8 and F9. Second, they performed data augmentation by randomly shifting the training images by various offsets, flipping them horizontally, and changing the lighting conditions.
 
<h2>ZFNet</h2>
 
<figure>&nbsp;</figure>
 
<ul>
 <li>ZFNet is another 8-layer CNN architecture.</li>
 <li>ZFNet is largely similar to AlexNet, with the exception of a few of the layers.</li>
 <li>ZFNet CNN architecture won the 2013 ImageNet ILSVRC challenge.</li>
 <li>One major difference in the approaches was that ZF Net used 7x7 sized filters whereas AlexNet used 11x11 filters.</li>
 <li>The intuition behind this is that by using bigger filters we were losing a lot of pixel information, which we can retain by having smaller filter sizes in the earlier convolution layers.</li>
 <li>The number of filters increases as we go deeper. This network also used ReLUs for their activation and trained using batch stochastic gradient descent.</li>
</ul>
<h2>VGGNet</h2>
 
<figure>&nbsp;</figure>
 
<ul>
 <li>The runner-up in the ILSVRC 2014 challenge was VGGNet.</li>
 <li>It was developed by K. Simon‐yan and A. Zisserman.</li>
 <li>During the design of the VGGNet, it was found that alternating convolution &amp; pooling layers were not required. So VGGnet uses multiple Convolutional layers in sequence with pooling layers in between.</li>
 <li>It had a very simple and classical architecture, with 2 or 3 convolutional layers, a pooling layer, then again 2 or 3 convolutional layers, a pooling layer, and so on (with a total of just 16 convolutional layers), plus a final dense net‐work with 2 hidden layers and the output layer. It used only 3 × 3 filters, but many filters.</li>
</ul>
<h2>GoogLeNet</h2>
<h2> </h2>
<figure>&nbsp;</figure>
 
<ul>
 <li>The GoogLeNet architecture was developed by Christian Szegedy et al. from Google Research,12 and it won the ILSVRC 2014 challenge by pushing the top-5 error rate below 7%.</li>
 <li>This great performance came in large part from the fact that the network was much deeper than previous CNNs</li>
 <li>This was made possible by sub-networks called inception modules, which allow GoogLeNet to use parameters much more efficiently than previous architectures: GoogLeNet actually has 10 times fewer parameters than AlexNet (roughly 6 million instead of 60 million).</li>
</ul>
 
<figure>&nbsp;</figure>
 
GoogLeNet uses 9 inception modules and it eliminates all fully connected layers using average pooling to go from 7x7x1024 to 1x1x1024. This saves a lot of parameters.
Several variants of the GoogLeNet architecture were later proposed by Google researchers, including Inception-v3 and Inception-v4, using slightly different inception modules, and reaching even better performance.
 
<h2>ResNet</h2>
<h2> </h2>
<figure>&nbsp;</figure>
 
<ul>
 <li>The ILSVRC 2015 challenge was won using a Residual Network (or ResNet)</li>
 <li>It was developed by Kaiming He et al.</li>
 <li>It delivered an astounding top-5 error rate under 3.6%, using an extremely deep CNN composed of 152 layers. It confirmed the general trend: models are getting deeper and deeper, with fewer and fewer parameters. The key to being able to train such a deep network is to use skip connections (also called shortcut connections): the signal feeding into a layer is also added to the output of a layer located a bit higher up the stack. Let’s see why this is useful.</li>
</ul>
 
<figure>&nbsp;</figure>
 
When training a neural network, the goal is to make it model a target function h(x). If you add the input x to the output of the network (i.e., you add a skip connection), then the network will be forced to model f(x) = h(x)-x rather than h(x). This is called residual learning.

Author

These 7 architectures are the winners of the Imagenet challenge.

7 CNN Architectures Evolved from 2010–2015

AI… is not new at all! Is not discovered only now on Smartphones or PCs. According to Wikipedia, the field of AI research was founded at a workshop held on the campus of Dartmouth College during the summer of 1956. (I wasn’t even born).

In the same year, Dartmouth College took a conference called “The Dartmouth Conference” and was organized by Marvin Minsky, John McCarthy, and two senior scientists: Claude Shannon and Nathan Rochester from IBM.

“Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it.” they said in the conference.

They thought that AI could be acting and thinking like a real Human after only one generation, is obvious that they were underestimating the difficulty of developing and improving this type of technology.

The “father” of AI is John McCarthy who coined the term of Artificial Intelligence. With the invention of AI they wanted to:

1st — create a system that could efficiently solve problems by limiting the search

2nd — construct a system that can learn by itself.

One of the results of the intensified research in AI was a novel program called The General Problem Solver, developed by Newell and Simon in 1957. It was capable of solving a greater extent of common sense problems.

Obviously, to have the AI as we know it today, a lot of time was spent in research and development. Let’s see the Timeline of the AI from 1956 until 2018 (Credit of this timeline to Wikipedia):

1956/57 — As we said in chapter 1, John McCarthy invented “The General Problem Solver”.

1958 — John McCarthy (Massachusetts Institute of Technology or MIT) invented the Lisp programming language.

1959 — John McCarthy and Marvin Minsky founded the MIT AI Lab.

1961 — James Slagle (Ph.D. dissertation, MIT) wrote (in Lisp) the first symbolic integration program, SAINT, which solved calculus problems at the college freshman level.

1964 — Danny Bobrow’s dissertation at MIT (technical report #1 from MIT’s AI group, Project MAC), shows that computers can understand natural language well enough to solve algebra word problems correctly. / Bertram Raphael’s MIT dissertation on the SIR program demonstrates the power of a logical representation of knowledge for question-answering systems.

1965 — Joseph Weizenbaum(MIT) built ELIZA, an interactive program that carries on a dialogue in the English language on any topic. It was a popular toy at AI centers on the ARPANET when a version that “simulated” the dialogue of a psychotherapist was programmed.

1968 — Richard Greenblatt (programmer) at MIT built a knowledge-based chess-playing program, MacHack, that was good enough to achieve a class-C rating in tournament play.

1975 — Barbara Grosz (SRI) established limits to traditional AI approaches to discourse modeling. Subsequent work by Grosz, Bonnie Webber, and Candace Sidner developed the notion of “centering”, used in establishing the focus of discourse and anaphoric references in Natural language processing.

1979 — Jack Myers and Harry Pople at the University of Pittsburgh developed INTERNIST, a knowledge-based medical diagnosis program based on Dr. Myers’ clinical knowledge.

1981 — Danny Hillis designs the connection machine, which utilizes Parallel computing to bring new power to AI, and computation in general. (Later founds Thinking Machines Corporation)

1985 — Neural Networks become widely used with the Backpropagation algorithm, also known as the reverse mode of automatic differentiation published by Seppo Linnainmaa in 1970 and applied to neural networks by Paul Werbos.

1987 — Commercial launch of generation 2.0 of Alacrity by Alacritous Inc./Allstar Advice Inc. Toronto, the first commercial strategic and managerial advisory system. The system was based upon a forward-chaining, a self-developed expert system with 3,000 rules about the evolution of markets and competitive strategies and co-authored by Alistair Davidson and Mary Chung, founders of the firm with the underlying engine developed by Paul Tarvydas. The Alacrity system also included a small financial expert system that interpreted financial statements and models.

1989 — The development of metal–oxide–semiconductor(MOS) very-large-scale integration(VLSI), in the form of complementary MOS(CMOS) technology, enabled the development of practical artificial neural network(ANN) technology in the 1980s. A landmark publication in the field was the 1989 book Analog VLSI Implementation of Neural Systems by Carver A. Mead and Mohammed Ismail.

1992 — Carol Stoker and NASA Ames robotics team explore marine life in Antarctica with an undersea robot TelepresenceROVoperated from the ice near McMurdo Bay, Antarctica, and remotely via satellite link from Moffett Field, California.

1994 — Lotfi Zadeh at U.C. Berkeley creates “soft computing”[49]and builds a world network of research with a fusion of neural science and neural net systems, fuzzy set theory and fuzzy systems, evolutionary algorithms, genetic programming, and chaos theory and chaotic systems. / English draughts(checkers) world champion Tinsleyresigned a match against computer program Chinook. Chinook defeated 2nd highest rated player, Lafferty. Chinook won the USA National Tournament by the widest margin ever.

1995 — One of Ernst Dickmanns’ robot cars (with robot-controlled throttle and brakes) drove more than 1000 miles from Munich to Copenhagen and back, in traffic, at up to 120 mph, occasionally executing maneuvers to pass other cars (only in a few critical situations a safety driver took over). The active vision was used to deal with rapidly changing street scenes.

1997 — First official RoboCup football (soccer) match featuring table-top matches with 40 teams of interacting robots and over 5000 spectators.

1998 — Ulises Cortés and Miquel Sànchez-Marrèorganize the first Environment and AI Workshop in Europe ECAI, “Binding Environmental Sciences and Artiﬁcial Intelligence.”

2000 — Interactive robopets (“smart toys”) become commercially available, realizing the vision of the 18th-century novelty toy makers. / Cynthia Breazeal at MIT publishes her dissertation on Sociable machines, describing Kismet (robot), with a face that expresses emotions.

2002 — iRobot’s Roombaautonomously vacuums the floor while navigating and avoiding obstacles.

2004 — NASA’s robotic exploration rovers Spirit and Opportunityautonomously navigate the surface of Mars.

2005 — Honda’s Asimo robot, an artificially intelligent humanoid robot, can walk as fast as a human, delivering trays to customers in restaurant settings. / Blue Brain is born, a project to simulate the brain at molecular detail.

2007 — DARPA launches the Urban Challenge for autonomous cars to obey traffic rules and operate in an urban environment.

2009 — Google builds an autonomous car.

2010 — Microsoft launched Kinect for Xbox 360, the first gaming device to track human body movement, using just a 3D camera and infra-red detection, enabling users to play their Xbox 360 wirelessly. The award-winning machine learning for human motion capture technology for this device was developed by the Computer Vision group at Microsoft Research, Cambridge.

2011 — IBM’s Watson computer defeated the television game show jeopardy!champions Rutter and Jennings.

2013 — Robot HRP-2 built by SCHAFT Inc of Japan, a subsidiary of Google, defeats 15 teams to win DARPA’s Robotics Challenge Trials. HRP-2 scored 27 out of 32 points in 8 tasks needed in disaster response. Tasks have driven a vehicle, walk over debris, climb a ladder, remove debris, walk through doors, cut through a wall, close valves, and connect a hose.

2011–2014 — Apple’s Siri(2011), Google’s Google Now(2012), and Microsoft’s Cortana (2014) are smartphone apps that use natural language to answer questions, make recommendations, and perform actions.

2015 — An open letter to ban the development and use of autonomous weapons signed by Hawking, Musk, Wozniakand 3,000 researchers in AI and robotics.

2016 — Google DeepMind’s AlphaGo defeated 3 time European Go champion 2 dan professional Fan Hui by 5 games to 0.

2017 — Deepstack is the first published algorithm to beat human players in imperfect information games, as shown with statistical significance on heads-up no-limit poker. Soon after, the poker AI Libratus by different research groups individually defeated each of its 4 human opponents — among the best players in the world — at an exceptionally high aggregated winrate, over a statistically significant sample. In contrast to Chess and Go, Poker is an imperfect information game.

2018 — Alibaba language processing AI outscores top humans at a Stanford University reading and comprehension test, scoring 82.44 against 82.304 on a set of 100,000 questions. (2) The European Lab for Learning and Intelligent Systems (aka Ellis) proposed as a pan-European competitor to American AI efforts, intending to stave off a brain drain of talent, along the lines of CERN after World War II. (3) Announcement of Google Duplex, a service to allow an AI assistant to book appointments over the phone. The LA Times judges the AI’s voice to be a “nearly flawless” imitation of human-sounding speech.

This is roughly the Timeline of the AI discoveries until 2018, very near to nowadays. The concept of a mechanic human was thought about thousands of years ago, look at AI now.

Humanoid and robots are more and more developed and they’re helping us in every field today. AI is now in every mobile phone, just ask “Hey Siri” or “Ok Google” and it’ll respond to you in a smart way (not always).

On iPhones there are Siri Suggestions: AI of the iPhone studies your behavior, which and how much you open an app, to suggest it to you once you need it.

(I wanted to take only the most important discoveries of the AI from this Timeline, hope you liked it.)

As we’ve seen, we had very different ways to let the machine learn something and do it by itself for us. Let’s say that AI is a human: In the beginning, as a kid, he learned his language.

Once he grows a bit he learned how to do math operations.

He’s a teenager and he learned how to speak to us like a real human and how to play some games such as chess and many more.

Now he grew more and he crossed the major age, let’s say he’s 20 years old now; he learned our attitudes and on this basis, he offers to us some ads about products that we may are interested in, besides of that he’s trying to learn how to drive a car by itself.

Now he’s 30 and he knows how to drive a car, solve problems and math algorithms, suggest to us products, places, restaurants, drive a car autonomously, and speak to us as a real human.

In a very short way, this is the main evolution of AI and is impressive how powerful is today this technology.

Actually, I’m writing this series with a device based on AI…but, it cannot do anything by itself obviously. AI without a human to use it’s useless. That’s one of many reasons why technology cannot replace humans.

AI was developed to help us not to replace us, and on the daily basis, we can see clearly that it simplified our lives a lot comparing nowadays roughly to 50 years ago.

We have a lot of intelligent devices all around the world, like autonomous cars, smartphones, home devices, and so on. But let’s think about, how it’ll be after 10 years, so in 2030? Will the AI explode more than today? Or the vintage will win this match, and the world will refuse this technology?

Technically, AI is exploding right now. The USA raised 4.4 billion $ on 155 investments and China 4.9 billion from 149 investments. This lets us know that in the upcoming years it’ll be a world made about AI-only devices more than today.

We will (maybe) see BMW or any other automotive company, releases its new autonomous car, maybe more humanoids, and more self hotels and other services, in fewer words, the life will be easier than today.

But what about our habits? They’ll change? Of course, but not all of them.

Let’s say that if we used to go to McDrive to pick up something to eat is possible that we’ll talk to a robot instead of the girl/boy, and many more. These are the only hypothesis and no one knows the future actually, maybe the vintage will win this match and the entire humanity will refuse the excess of technology. Who knows?

Tech Writer, Content Creator & SMM

Why AI? What’s the Goal of this innovation?


AI, What’s The Final Goal?

Google has launched a new educational and professional program called “Google Career Certificates”. 

This courses actually were ideated at the beginning for IT fields, then it expands to others. Now “The Giant G” wanted to improve this service including “Project Manager” and more fields, the most impressive thing is that in only 6 months course you’ll be certified (and get the certificate) at your field as you were in university. In fewer words, what you study in 4 years of university, you can do it in 6 months thanks to Google Service.

This is, from my point of view, the beginning of a new age of information, education, and careers. They’re focusing on getting a job. The motto is “Get Certificate, Get a Job!”. The next available courses are the following:

And the available course now on Coursera is:

Google IT Support Specialist (With Professional Certificate)

Note: For more info about the courses and to be informed on when they’ll be available visit the official website, you can also signup to their newsletter to be always up to date for new releases.


Yes! You can have a University like a degree in 6 months for a maximum cost of only 300 bucks! That’s revolutionary, and it helps a lot the job seekers! Personally, I’m interested in the Data Analyst and Project Manager fields, I’m curious about what you’ll be interested in! These courses will be hosted by Coursera, you can enroll for free or with a premium membership. 


Everything seems awesome but what I’ll be able to do after these courses? And what is the average annual salary for each of these new professions? Let’s see together all these details (credits to Google):

Data Analyst: Data analysts make use of data to help inform important business decisions. They prepare, process, and analyze data for key insights, share their findings with stakeholders, and provide data-driven recommendations for effective action. This certificate focuses on the foundations of traditional project management, while also offering insight into agile project management. $66,000 is the median annual wage for data analysts


Project Manager: Project managers are responsible for planning and overseeing projects to ensure they are completed efficiently with maximum quality and value-added to the business. This certificate focuses on the foundations of traditional project management, while also offering insight into agile project management. $93,000 is the median annual wage for project managers


UX Designer: User experience (UX) designers make technology easier and more enjoyable to use. They create or refine products and interfaces to make them useful, usable, and accessible to users. This certificate teaches learners the foundations of UX design and research, building low-fidelity designs and wireframes, creating high-fidelity prototypes, and testing. $75,000 is the median annual wage for UX designers.


IT Support Specialist: IT support is all about troubleshooting and problem solving when technology fails us and providing great customer service along the way. Specialists support everything from networking to operating systems, and system administration to security in the workplace. 80% of learners in our Google IT Support Professional Certificate program in the U.S. report a career impact within 6 months, such as finding a new job, getting a raise, or starting a new business. $54,760 is the median annual wage for IT support specialists.

that you’ll (maybe) have the chance to work for Google also and not only with other big companies, once you’ve received their certificate. This is a bit believable because the teachers of these courses, are actually Google employees, and who better than them can teach us how it works inside one of the biggest tech companies in the world?


Google has launched a new educational and professional program called “Google Career Certificates”.&nbsp;
 
This courses actually were ideated at the beginning for IT fields, then it expands to others. Now “The Giant G” wanted to improve this service including “Project Manager” and more fields, the most impressive thing is that in only 6 months course you’ll be certified (and get the certificate) at your field as you were in university. In fewer words, what you study in 4 years of university, you can do it in 6 months thanks to Google Service.
 
This is, from my point of view, the beginning of a new age of information, education, and careers. They’re focusing on getting a job. The motto is “Get Certificate, Get a Job!”. The next available courses are the following:
 
<ul>
 <li>Data Analyst;</li>
 <li>Project Manager;</li>
 <li>UX Designer.</li>
</ul>
And the available course now on Coursera is:
<ul>
 <li>Google IT Support Specialist (With Professional Certificate)</li>
</ul>
Note: For more info about the courses and to be informed on when they’ll be available visit the <a href="https://grow.google/certificates/" rel="noopener nofollow">official website</a>, you can also signup to their newsletter to be always up to date for new releases.
 
 
<figure>&nbsp;</figure>
 
 
<h2>Is This Really Worth It?</h2>
 
Yes! You can have a University like a degree in 6 months for a maximum cost of only 300 bucks! That’s revolutionary, and it helps a lot the job seekers! Personally, I’m interested in the Data Analyst and Project Manager fields, I’m curious about what you’ll be interested in! These courses will be hosted by <a href="https://www.coursera.org/" rel="noopener nofollow">Coursera</a>, you can enroll for free or with a premium membership.&nbsp;
 
 
 
<h2>Courses Details</h2>
 
Everything seems awesome but what I’ll be able to do after these courses? And what is the average annual salary for each of these new professions? Let’s see together all these details (credits to Google):
 
Data Analyst: Data analysts make use of data to help inform important business decisions. They prepare, process, and analyze data for key insights, share their findings with stakeholders, and provide data-driven recommendations for effective action. This certificate focuses on the foundations of traditional project management, while also offering insight into agile project management. $66,000 is the median annual wage for data analysts 

Project Manager: Project managers are responsible for planning and overseeing projects to ensure they are completed efficiently with maximum quality and value-added to the business. This certificate focuses on the foundations of traditional project management, while also offering insight into agile project management. $93,000 is the median annual wage for project managers 

UX Designer: User experience (UX) designers make technology easier and more enjoyable to use. They create or refine products and interfaces to make them useful, usable, and accessible to users. This certificate teaches learners the foundations of UX design and research, building low-fidelity designs and wireframes, creating high-fidelity prototypes, and testing. $75,000 is the median annual wage for UX designers. 

IT Support Specialist: IT support is all about troubleshooting and problem solving when technology fails us and providing great customer service along the way. Specialists support everything from networking to operating systems, and system administration to security in the workplace. 80% of learners in our Google IT Support Professional Certificate program in the U.S. report a career impact within 6 months, such as finding a new job, getting a raise, or starting a new business. $54,760 is the median annual wage for IT support specialists.
 
 
 
 
<figure>&nbsp;</figure>
 
 
 
<h2>Some rumors say:</h2>
that you’ll (maybe) have the chance to work for Google also and not only with other big companies, once you’ve received their certificate. This is a bit believable because the teachers of these courses, are actually Google employees, and who better than them can teach us how it works inside one of the biggest tech companies in the world?

Google is moving into a new teaching technology!


Google Career Certificates: 6 Months Equal to 4 Years University

And here we are in a new article where we will talk about WWDC 2020, the annual event that holds Apple for developers who usually announce the release of Beta versions for the new types of iOS, iPadOS, macOS, watchOS and tvOS. 

If you’re a developer, you’ll be able to use these trial versions to give Apple valuable feedback for its improvement as well as for the bug fix, so that it will be officially presented in September together with the new iPhone, iPad, Mac, Apple Watch and Apple TV for the public, for now, is available the Developer Beta, in July though it’ll be available the Public Beta release.

Usually, the Keynote was always held at the Apple headquarters in Cupertino with a lot of live viewers, but for obvious reasons this year, it was decided to record it and air it on June 22 at the Apple Park. What can I say, there is a lot of news that (finally) have arrived with these updates.

But let’s not get chatty and let’s get started!

The 14th version of the Cupertino company’s operating system looks like a much-improved iOS 13, now let’s see what’s new in this update.

Finally, after years and years that Apple always focused on the same minimalist design, it decided to change and introduce widgets, fundamental components on the Android operating system already present since the first versions. 

These Widgets as well as being in the appropriate tab (the last page on the left on the homepage) will also be possible to integrate into the screen along with the installed apps, in a few words they will be like this (the image above👆)

How many times, for iPhone owners, have we had to scroll through pages and pages on the home screen to find an app we need? Or using the spotlight search?

In this version of the operating system, the App Library will be introduced for the first time in the history of iOS.
But how do this works?

Go to the last page of the home screen and scroll to the left once more to open this screen (the image above👆)

A real collection of our apps and all divided by category, in a few words it’s like a giant folder with all our apps. There will also be suggestions and recently installed apps that will decide your phone thanks to its artificial intelligence. 

Along with this modification, you’ll be able to show or hide the home pages so you’ll have a phone with a more customizable and minimal interface, in any case, we’ll have the apps in our new library. 

- That is really more similar to the Android drawer, but let’s go ahead. -

Exactly! Enough with the invasive Siri screen that didn’t allow us to do anything and wait for our virtual best friend to finish.

iOS 14 from what you can see is very much focused on the graphical view and customization of it, in fact, Apple has been working on features that actually already had to improve them.

But back to Siri. Our voice assistant will appear much less invasive than before by making its “Sphere” appear at the bottom center with an animation. To give you a better idea, it will look like this (the image above👆).

Once you ask Siri what you need, she will show you the result with a small popup, as if it were a notification. Siri will be able to translate even more languages understanding its meaning and not as a literal translation.

Speaking of translations, after years that Google has released Google Translate, finally, the rival company decides to develop and introduce a new app for text and conversation translation. 

The app is in fact called Translate and can automatically identify the language you want to translate, even vocally. What will the app look like? Here it is (the image above👆)

You’ll be able to start conversations and with its AI it’ll identify automatically which language are you speaking and which one is the other guy/girl speaking. Impressive!

How many of you have been bothered at least once by the super invasive full-screen view during incoming calls? Basically, if I didn’t want to answer someone I’d have to wait for the call to close by itself to use my mobile again, what stress!

Instead now (once again, finally) they have introduced a popup that goes down from top to bottom with 2 commands:
- Answer;
- End the call;

So you’ll be able to snub anyone and in the meantime use your mobile phone 😂

App Clips are snippets of apps up to 10 MB in size that allow us to perform a certain action without having to install the entire application. 

After finishing, the App Clip will self-delete. Let’s say, for example, that you find an electric scooter in the city and it is supported for App Clips; to use it you should use the app, but not anymore with this update, so you just need to identify the QR code of the same or even just approaching the mobile phone and you’re done

Now our mobile phone is also our car key. Just enter some data in the installation procedure, a bit like credit cards in Apple Wallet, and voilà! 

You can do all the classic key operations but with your smartphone. In addition, you can send by message with iMessage the file where it contains the key data so you can share it with family and friends.

And here we are in a new article where we will talk about WWDC 2020, the annual event that holds Apple for developers who usually announce the release of Beta versions for the new types of iOS, iPadOS, macOS, watchOS and tvOS.&nbsp;
 
If you’re a developer, you’ll be able to use these trial versions to give Apple valuable feedback for its improvement as well as for the bug fix, so that it will be officially presented in September together with the new iPhone, iPad, Mac, Apple Watch and Apple TV for the public, for now, is available the Developer Beta, in July though it’ll be available the Public Beta release.
 
Usually, the Keynote was always held at the Apple headquarters in Cupertino with a lot of live viewers, but for obvious reasons this year, it was decided to record it and air it on June 22 at the Apple Park. What can I say, there is a lot of news that (finally) have arrived with these updates.
 
But let’s not get chatty and let’s get started!
 
<h2>iOS 14</h2>
The 14th version of the Cupertino company’s operating system looks like a much-improved iOS 13, now let’s see what’s new in this update.
 
 
 
<h2>Widgets</h2>
 
 
<figure>&nbsp;</figure>
 
Finally, after years and years that Apple always focused on the same minimalist design, it decided to change and introduce widgets, fundamental components on the Android operating system already present since the first versions.&nbsp;
 
These Widgets as well as being in the appropriate tab (the last page on the left on the homepage) will also be possible to integrate into the screen along with the installed apps, in a few words they will be like this (the image above👆)
 
 
<h2>App Library</h2>
 
 
<figure>&nbsp;</figure>
 
 
How many times, for iPhone owners, have we had to scroll through pages and pages on the home screen to find an app we need? Or using the spotlight search?
 
In this version of the operating system, the App Library will be introduced for the first time in the history of iOS. 
But how do this works?
 
Go to the last page of the home screen and scroll to the left once more to open this screen (the image above👆)
 
A real collection of our apps and all divided by category, in a few words it’s like a giant folder with all our apps. There will also be suggestions and recently installed apps that will decide your phone thanks to its artificial intelligence.&nbsp;
 
Along with this modification, you’ll be able to show or hide the home pages so you’ll have a phone with a more customizable and minimal interface, in any case, we’ll have the apps in our new library.&nbsp;
 
- That is really more similar to the Android drawer, but let’s go ahead. -
 
 
 
<h2>Siri</h2>
 
<figure>&nbsp;</figure>
Exactly! Enough with the invasive Siri screen that didn’t allow us to do anything and wait for our virtual best friend to finish.
 
iOS 14 from what you can see is very much focused on the graphical view and customization of it, in fact, Apple has been working on features that actually already had to improve them.
 
But back to Siri. Our voice assistant will appear much less invasive than before by making its “Sphere” appear at the bottom center with an animation. To give you a better idea, it will look like this (the image above👆).
 
Once you ask Siri what you need, she will show you the result with a small popup, as if it were a notification. Siri will be able to translate even more languages understanding its meaning and not as a literal translation.
 
 
 
<h2>Translate!</h2>
 
 
<figure>&nbsp;</figure>
Speaking of translations, after years that Google has released Google Translate, finally, the rival company decides to develop and introduce a new app for text and conversation translation.&nbsp;
 
The app is in fact called Translate and can automatically identify the language you want to translate, even vocally. What will the app look like? Here it is (the image above👆)
 
You’ll be able to start conversations and with its AI it’ll identify automatically which language are you speaking and which one is the other guy/girl speaking. Impressive!
 
 
 
<h2>Incoming Call? No Problem!</h2>
 
 
<figure>&nbsp;</figure>
How many of you have been bothered at least once by the super invasive full-screen view during incoming calls? Basically, if I didn’t want to answer someone I’d have to wait for the call to close by itself to use my mobile again, what stress!
 
Instead now (once again, finally) they have introduced a popup that goes down from top to bottom with 2 commands: 
- Answer; 
- End the call;
 
So you’ll be able to snub anyone and in the meantime use your mobile phone 😂
 
 
 
 
<h2>App Clips</h2>
 
 
<figure>&nbsp;</figure>
App Clips are snippets of apps up to 10 MB in size that allow us to perform a certain action without having to install the entire application.&nbsp;
 
After finishing, the App Clip will self-delete. Let’s say, for example, that you find an electric scooter in the city and it is supported for App Clips; to use it you should use the app, but not anymore with this update, so you just need to identify the QR code of the same or even just approaching the mobile phone and you’re done
 
 
 
<h2>Car Keys On Your Phone</h2>
 
 
<figure>&nbsp;</figure>
 
Now our mobile phone is also our car key. Just enter some data in the installation procedure, a bit like credit cards in Apple Wallet, and voilà!&nbsp;
 
You can do all the classic key operations but with your smartphone. In addition, you can send by message with iMessage the file where it contains the key data so you can share it with family and friends.
 
There will be different levels of access that will be established by the car manufacturer and Apple, but mainly will be full access (i.e. as if I had the copy of the original keys), and partial access that will allow only the opening of the doors but without the ability to start the car engine. Of course, all operations will be totally secure thanks to FaceID or TouchID access.
 
The car manufacturers who have participated for now are BMW and Ford with the new 2021 models, BMW announced that in the BMW 5 Series 2021 will be available car — mobile phone coupling.&nbsp;
 
Other car companies will also join in the future.
 
 
<h2> </h2>
<h2>Apple CarPlay</h2>
 
 
<figure>&nbsp;</figure>
 
CarPlay just decided to “beautify” it a little bit. With iOS14 it will be possible to insert a background and dark mode will be available. That’s it 😊
 
 
 
<h2>iMessage</h2>
 
<figure>&nbsp;</figure>
An eagerly awaited feature for all iMessage users, the ability to reply to messages! It could be done for a lifetime on Whatsapp, Telegram, and lately also on Messenger, but on iMessage introduces it with the new operating system.
 
And not only that, but you can also fix the conversations at the top with very nice graphics by scrolling to the right and pressing the pin icon.
 
Apple has also updated the group conversations, giving you the ability to add photos of participants. In addition, it will be possible to recall someone in the chat by writing only their name and, if the notifications are muted for the group, only those in which you will be recalled by someone in a discussion will appear.
 
 
 
 
<h2>Memoji</h2>
 
 
<figure>&nbsp;</figure>
Beautiful memojis have impressed most iPhone users.&nbsp;
 
They’re a nice way to express things we couldn’t say in words or reactions that wouldn’t be fully understood with a simple emoji. In fact, new memojis will be coming along with this update, new accessories, you can change the age and there will also be facial coverage, in simple terms, the mask!&nbsp;
 
 
 
<h2>Maps</h2>
 
 
<figure>&nbsp;</figure>
Google Maps rival, Maps, has been further updated to improve the travel experience, which also introduces the route of a cycling destination.
 
&nbsp;As you can already choose how to travel our route (car, walk, transportation) we will also add the bike that will show a dedicated route for it, which will mainly trace the destination on bike paths and roads suitable for the circulation of the same.
 
The second new feature of Maps is that it will give us detailed information about our route. This kind of detail will be for walking and cycling trips and will show us if the route has ups and downs, ruined roads, or if it is linear. This information will be available on Apple Watch is connected.&nbsp;
 
There will also be a map guide that will allow us to find new places and locations in the area where we are located. 
PS: It will also warn us about speed cameras on the road.
 
The third new feature of the app is the integration of charging stations for electric cars along the way. In practice you can connect your electric car to your mobile phone and your iPhone will be able to know how much battery is available and at what distance you need to charge your car.&nbsp;
 
Very useful if you plan to make long trips in a fully electric car like Tesla.
 
 
 
 
<h2>Picture in Picture (PiP)</h2>
 
 
<figure>&nbsp;</figure>
Our dearly beloved QuickTime player on the iPhone has always had one flaw…that of not being able to overlay the video or movie we’re watching while we’re doing something else.
 
&nbsp;Apparently, Apple noticed this and finally introduced it to this iOS 14. Trying it with the Developer Beta version, I noticed that it’s very fluid and doesn’t have any bugs yet. A very useful feature if you want to continue a video while writing a message to someone else or whatever you want to do.&nbsp;
 
It will be a little icon at the top left of the player that will allow us to reduce the size of the video and overlay it.

WWDC 2020, the annual event that holds Apple for developers who usually announce the release of Beta versions for the new types of iOS, iPadOS, macOS, watchOS and tvOS.

iOS 14, The Last Update of iOS This Year

Going back with the years, we’ve learned that when a big company does a new project or even a new behavior, most of the rival companies will do the same. It doesn't matter really when they're coping but that’s how trends are created.

Let’s get more specific about what I mean, but to do that I need to dust off some past events.

Obviously, everyone knows how limited and minimal are the main screens of the iPhone, and that (before the iOS 14 update) it doesn’t have a drawer. What happened just some years after releasing the first iPhone? Huwaei comes in with their UI and is not the only one, to name a few we have also Xiaomi and Oppo. The minimal theme of the user interface ensures a less RAM consumption.

Another one is when Apple Pay was launched, no one of the famous smartphones companies did it immediately, except for some companies in China like WeChat, Xiaomi with its own wallet app, and many more. What happened next? I saw advertising about Samsung Pay and Google Pay. So it's transformed into a trend.

But why am I mention Apple so often? Because this is the main argument, the iPhone.

Let’s analyze it a bit. Apple just revealed on the 13th of October the dates of the iPhone 12 launch. On the 23rd of October, it’ll be released the iPhone 12 but for the Pro and Mini versions, we must wait until the 13th of November.

In the presentation of the Cupertino’s company device, CEO Tim Cook, announced that the boxes of the iPhone will be thinner, “lighter”.

In the iPhone box, we will have obviously the phone but we will not have the charger and the EarPods. We receive the USB C-Lightning for the fast charging. Apple says that this is due to the excessive amount of electronic waste in the world.

“In carbon emissions, it’s like taking 450,000 cars off the roads every year”, Apple said.

It doesn’t matter actually if this is right or wrong, or even if they’re lying or saying the truth. This is the beginning of a new way to sell Smartphones and to sell their accessories. Is just a matter of time that other companies will see that this strategy is working and (maybe) will see that other companies will do the same thing with their products. So another trend is about to be created.

With this strategy, the marketing of Smartphones will totally change to be good at the environment or to sell you some accessories produced but less sold.

Reply with your thoughts about this topic, and if you think the same, just share it. 

Going back with the years, we’ve learned that when a big company does a new project or even a new behavior, most of the rival companies will do the same. It doesn't matter really when they're coping but that’s how trends are created.
 
Let’s get more specific about what I mean, but to do that I need to dust off some past events.
 
Obviously, everyone knows how limited and minimal are the main screens of the iPhone, and that (before the iOS 14 update) it doesn’t have a drawer. What happened just some years after releasing the first iPhone? Huwaei comes in with their UI and is not the only one, to name a few we have also Xiaomi and Oppo. The minimal theme of the user interface ensures a less RAM consumption.
 
<figure>&nbsp;</figure>
 
Another one is when Apple Pay was launched, no one of the famous smartphones companies did it immediately, except for some companies in China like WeChat, Xiaomi with its own wallet app, and many more. What happened next? I saw advertising about Samsung Pay and Google Pay. So it's transformed into a trend.
 
<figure>&nbsp;</figure>
 
But why am I mention Apple so often? Because this is the main argument, the iPhone.
 
Let’s analyze it a bit. Apple just revealed on the 13th of October the dates of the iPhone 12 launch. On the 23rd of October, it’ll be released the iPhone 12 but for the Pro and Mini versions, we must wait until the 13th of November.
 
In the presentation of the Cupertino’s company device, CEO Tim Cook, announced that the boxes of the iPhone will be thinner, “lighter”.
 
<figure>&nbsp;</figure>
 
In the iPhone box, we will have obviously the phone but we will not have the <a href="https://medium.com/y-technology/whats-happening-apple-d9ae60a8b982" target="_blank">charger and the EarPods.</a> We receive the USB C-Lightning for the fast charging. Apple says that this is due to the excessive amount of electronic waste in the world.
 
 
<h2>“In carbon emissions, it’s like taking 450,000 cars off the roads every year”, Apple&nbsp;said.</h2>
 
It doesn’t matter actually if this is right or wrong, or even if they’re lying or saying the truth. This is the beginning of a new way to sell Smartphones and to sell their accessories. Is just a matter of time that other companies will see that this strategy is working and (maybe) will see that other companies will do the same thing with their products. So another trend is about to be created.
 
With this strategy, the marketing of Smartphones will totally change to be good at the environment or to sell you some accessories produced but less sold.
 
Reply with your thoughts about this topic, and if you think the same, just share it.&nbsp;
 
Cheers!

Once a big company began it, all the others sooner or later will copy.

The Next Big Tech Trend

When we develop some applications we have to deal with data. The data is a collection of values and for storing the collection of values we need data structures. CPP provides built-in libraries of classes for all these data structures and that collection of classes are called STL (Standard Template Libraries ).

Algorithms are the functions used to perform operations on containers

A container is a holder object that stores a collection of other objects. They are implemented as class templates, which allows great flexibility in the types supported as elements.

The container manages the storage space for its elements and provides member functions to access them, either directly or through iterators.

Many containers have several functions in common, and share functionalities. The decision of which type of container to use for a specific need does not generally depend only on the functionality offered by the container, but also on the efficiency of some of its members

<h1>Need of STL?</h1>
When we develop some applications we have to deal with data. The data is a collection of values and for storing the collection of values we need data structures. CPP provides built-in libraries of classes for all these data structures and that collection of classes are called STL (Standard Template Libraries ).
 
<h2>STL consists of</h2>
<ol>
 <li>ALgorithms</li>
 <li>Containers</li>
 <li>Iterators</li>
</ol>
<ul>
 <li>Algorithms are the functions used to perform operations on containers</li>
 <li>For example</li>
</ul>
<blockquote>sort()</blockquote>
<blockquote>reverse()</blockquote>
<blockquote>count()</blockquote>
<blockquote>find()</blockquote>
<blockquote>binary_search()</blockquote>
<blockquote>lower_bound()</blockquote>
<blockquote>upper_bound()</blockquote>
<blockquote>next_permutation()</blockquote>
<blockquote>prev_permutation()</blockquote>
<blockquote>distance()</blockquote>
 
<ul>
 <li>A container is a holder object that stores a collection of other objects. They are implemented as class templates, which allows great flexibility in the types supported as elements.</li>
 <li>The container manages the storage space for its elements and provides member functions to access them, either directly or through iterators.</li>
 <li>Many containers have several functions in common, and share functionalities. The decision of which type of container to use for a specific need does not generally depend only on the functionality offered by the container, but also on the efficiency of some of its members</li>
 <li>For example :</li>
</ul>
<blockquote>vector</blockquote>
<blockquote>list</blockquote>
<blockquote>forward_list</blockquote>
<blockquote>deque</blockquote>
<blockquote>priority_queue</blockquote>
<blockquote>stack</blockquote>
<blockquote>set</blockquote>
<blockquote>multiset</blockquote>
<blockquote>map</blockquote>
<blockquote>multimap</blockquote>
 
<ul>
 <li>An iterator is any object that, pointing to some element in a range of elements (such as an array or a <a href="https://www.cplusplus.com/stl" rel="noopener nofollow">container</a>), has the ability to iterate through the elements of that range using a set of operators (with at least the increment (<code>++</code>) and dereference (<code>*</code>) operators).</li>
 <li>The most obvious form of iterator is a pointer: A pointer can point to elements in an array and can iterate through them using the increment operator (<code>++</code>). But other kinds of iterators are possible. For example, each <a href="https://www.cplusplus.com/stl" rel="noopener nofollow">container</a> type (such as a <a href="https://www.cplusplus.com/list" rel="noopener nofollow">list</a>) has a specific iterator type designed to iterate through its elements.</li>
 <li>For example :</li>
</ul>
 
<blockquote>iterator</blockquote>
<blockquote>iterator_traits</blockquote>
<blockquote>reverse_iterator</blockquote>
<blockquote>move_iterator</blockquote>
<blockquote>back_insert_iterator</blockquote>
<blockquote>front_insert_iterator</blockquote>
<blockquote>insert_iterator</blockquote>
<blockquote>istream_iterator</blockquote>
<blockquote>ostream_iterator</blockquote>
<blockquote>input_iterator_tag</blockquote>
 
<h2>Example code with the definition of each container :</h2>
 
 
<figure>&nbsp;</figure>

This story is all about C++ STL which is a powerful set of c++ template classes o provide general-purpose classes and functions with templates.

Mario Guimarey

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